Effectiveness of COVID-19 shelter-in-place orders varied by state

Abstract

State "shelter-in-place" (SIP) orders limited the spread of COVID-19 in the U.S. However, impacts may have varied by state, creating opportunities to learn from states where SIPs have been effective. Using a novel dataset of state-level SIP order enactment and county-level mobility data form Google, we use a stratified regression discontinuity study design to examine the effect of SIPs in all states that implemented them. We find that SIP orders reduced mobility nationally by 12 percentage points (95% CI: -13.1 to -10.9), however the effects varied substantially across states, from -35 percentage points to +11 percentage points. Larger reductions were observed in states with higher incomes, higher population density, lower Black resident share, and lower 2016 vote shares for Donald J. Trump. This suggests that optimal public policies during a pandemic will vary by state and there is unlikely to be a "one-size fits all" approach that works best.

Fig 1. Regression discontinuity plot for the relationship between SIP implementation and community mobility.

Each dot is a binned daily average mobility relative to the baseline period. The trend-line is fit as a fourth order polynomial. Solid vertical line represents the relative date of SIP implementation.

Fig 2. State-specific regression discontinuity estimates.

Each dot is a coefficient estimate. Horizontal bars represent 95% confidence intervals.